Anjun Chen1 and Garret Washburn2, 1USA, 2California State Polytechnic University, USA
This research is intended to display and encapsulate a methodology for solving the problem of the desperate lack of information and resources for learning about and practicing opening moves in Chess. The methodology, GrandMaster Openings, comes in the shape of a mobile application available on both the Apple and Google Play stores and can be downloaded right now [1]. The GrandMaster Openings app seeks to give the user insightful information on opening moves in Chess, and even comes equipped with an AI chat feature with an AI GrandMaster trained on the same data that is on display for users to see within the app [2]. The most prominent technologies that were utilized to develop this application are ChatGPT’s trainable chat model features and the Flutter mobile application development framework, as well as a few extensive chess match datasets. During development, the creation and implementation of a back-end server was necessary, as the transmission of quite extensive data and the housing of a big AI model became cumbersome to keep on a user’s device, and proved to be quite challenging due to the new implications of a back-end server [3]. Within this essay are experiments that were conducted specifically targeted at the back-end server in order to discover any current or potential issues with it. Ultimately, after proper development and thorough review, the GrandMaster Openings mobile application is a great resource for those looking to learn more about Chess openings, get immediate feed from a trained AI model GrandMaster, and review excellently collected real life game data.
Chess, Opening, AI, LLM
